Research Scientist, Robotics
Listed on 2026-01-12
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Research/Development
Robotics, Research Scientist
Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.
Our base salary range is $167,030 - $260,570, and in addition we have generous bonus plans to provide a competitive compensation package.
Who You AreAs a Research Scientist on our team, you'll have the unique opportunity to develop and investigate core research problems in foundation models and skills for robotics, contribute to the development of completely open data sets, benchmarks, and models, and experiment with robots in the real world.
We are looking for applicants interested in robotics, with a focus on core techniques in robot manipulation, large scale training in simulated environments, vision-language-action models, and skill learning. International candidates are welcome to apply. Pay is competitive, and visa sponsorship is available.
We collaborate frequently with researchers on other Ai2 teams focused on embodied AI, computer vision, and natural language processing, among others. Our main office has close ties and unique access to researchers at the University of Washington, only 1.5 miles away. Researchers excited about such internal and external collaborations are encouraged to apply.
Research Scientists in the Robotics team will work on multiple exciting research projects in the above areas but can also contribute and engage in a variety of other activities critical to our research and mission. These include opportunities to lead select projects, mentor interns and pre-doctoral candidates, author and present scientific papers, and collaborate with researchers at other organizations including universities.
WhoWe Are
Ai2's Robotics team is led by Dieter Fox. The team aims to develop the simulation environments, data generation, and benchmarking skills that enable a rigorous and scientific investigation of the core building blocks and scaling properties of robot foundation models. The insights gained from these experiments will inform the development of truly capable foundation models for robots operating in the real world.
Areasof Work
- Robotics - Enable agents that safely navigate, manipulate objects, and follow instructions in simulation and in the real world (w/ real robots).
- Language & Vision - Make vision-language-action models more robust and capable.
- Open source projects - Make substantial contributions to the tools needed for robust, reproducible, and distributed experimentation.
We regularly publish in high-profile conferences and journals in robotics (CoRL, ICRA, RSS), computer vision (CVPR, ICCV, ECCV), and machine learning (e.g., NeurIPS, ICLR).
Your Next ChallengeAt Ai2, you will be working with world-class AI researchers and talented software engineers. We perform team-based, ambitious research, with a mandate to strive for big breakthroughs, not just incremental progress, in an exciting and interactive workplace.
All scientists have the opportunity to mentor interns (and other students) and will participate directly in Ai2's groundbreaking work. There are no restrictions on publications.
What You’ll NeedQualifications:
- A strong foundation (typically PhD level) in one or more of the following areas: robot manipulation, planning and motion generation, RL and imitation learning, real world robot systems, simulation environments and sim2real, vision-language-action models.
- A strong publication record in AI-related areas. Example venues include ICRA, RSS, CVPR, ICCV, ECCV, NeurIPS, ICLR, etc. Contributions to research communities (e.g. workshop organization, tutorials) are a plus.
- Strong software engineering skills. Experience working with real robot systems and/or with deep learning frameworks.
Bonus
Qualifications:
- Research experience in related areas like large-scale multi-node training, training dynamics, efficiency, data curation, multimodal model debugging, post-training methods, among others.
- Contributions to open-source research libraries.
The physical demands described here are representative of those that must be met by…
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